Methods and systems for intelligent AMF assignment to minimize re-direction

ABSTRACT

A method, a system, and a non-transitory storage medium are described in which an access and mobility management function (AMF) assignment service is provided. A network device receives an assignment policy for selecting an AMF from a group of available AMFs, wherein the assignment policy includes network slice priorities for available network slices in the RAN; stores the assignment policy; receives, during a registration procedure initiated by an end device, Network Slice Selection Assistance Information (NSSAI); identifies, from the NSSAI, multiple single-NSSAIs (S-NSSAIs); and selects, based on the assignment policy, an AMF for a highest priority S-NSSAI, of the multiple S-NSSAIs.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation of U.S. patent application Ser. No.17/061,777, filed on Oct. 2, 2020, which is a continuation of U.S.patent application Ser. No. 16/423,304 filed on May 28, 2019, bothentitled “Methods and Systems for Intelligent AMF Assignment to MinimizeRe-Direction,” the contents of which are hereby incorporated byreference.

BACKGROUND

Development and design of radio access networks (RAN) and core networkspresent certain challenges from a network-side perspective and an enddevice perspective. For example, depending on the configurations fromboth network-side and end device-side perspectives, such configurationsmay reduce the effective use of resources.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a diagram illustrating an exemplary environment in which anembodiment of an intelligent access and mobility management function(AMF) assignment service may be implemented;

FIG. 2 is a diagram illustrating components in a portion of theenvironment of FIG. 1 ;

FIG. 3A-3C are diagrams illustrating an exemplary process of anembodiment of the intelligent AMF assignment service;

FIG. 4 is a diagram illustrating an exemplary embodiment of an AMFassignment table for the intelligent AMF assignment service;

FIG. 5 is a signal flow diagram of an exemplary end device attachprocedure using the intelligent AMF assignment service, according to animplementation described herein;

FIG. 6 is a diagram illustrating exemplary components of a device thatmay correspond to one or more of the devices illustrated and describedherein; and

FIG. 7 is a flow diagram illustrating an exemplary process of anembodiment of the intelligent AMF assignment service, according to animplementation described herein.

DETAILED DESCRIPTION OF PREFERRED EMBODIMENTS

The following detailed description refers to the accompanying drawings.The same reference numbers in different drawings may identify the sameor similar elements. Also, the following detailed description does notlimit the invention.

Using network slicing, a physical network may be sectioned (or “sliced”)into multiple, virtual, end-to-end networks. Each network slice may bededicated for different types of services with different characteristicsand requirements (e.g., latency, voice, jitter, bandwidth, pricing,enterprise, etc.). As used herein, the term “slice” or “network slice”refers to a complete logical network including a Radio Access Network(RAN) and Core Network that provides certain telecommunication servicesand network capabilities that can vary from slice to slice. Selection ofnetwork slices can, thus, have significant impact on network performanceand user experience.

In some instances, user equipment (UE, also referred to herein as an enddevice) may be configured to use a particular network slice uponconnection to a network (e.g., a Fifth Generation (5G) network). Forexample, an Internet-of-Things (IoT) device may be designated with aparticular slice identifier that matches network slice characteristicsto the type of traffic generated by the IoT device. End devices thatconnect to the network may be assigned to an access and mobilitymanagement function (AMF) that performs registration management,connection management, etc., for the end device. There may be multipleAMF instances and each AMF instance (or a set of AMF instances) may beassociated with one or more network slices.

In current 5G networks, the RAN has information identifying a defaultAMF to associate with an end device during initial registration. Inaddition, the 5G core network may redirect the end device to a differentAMF or AMF set after determining the set of network slices that the enddevice is allowed to use, together with additional information such asslice availability in the current registration area, etc. Theseredirections consume additional network resources and introduce latencyin completing the initial attach process. Currently, there is noconsideration to address or minimize the amount of redirections.Furthermore, RAN conditions and core network conditions are not takeninto account during initial registration, which may result inoverloading of a default AMF or underutilization of a different AMF.

Systems and methods described herein provide capabilities in the RAN toperform intelligent AMF selection during initial registration, includinga framework by which RAN and core network conditions are factored intothe selection process. According to exemplary embodiments, anintelligent AMF assignment service is described. A network devicereceives an assignment policy for selecting an AMF from a group ofavailable AMFs, wherein the assignment policy includes network slicepriorities for available network slices in the RAN; stores theassignment policy; receives, during a registration procedure initiatedby an end device, Network Slice Selection Assistance Information(NSSAI); identifies, from the NSSAI, multiple single-NSSAIs (S-NSSAIs);and selects, based on the assignment policy, an AMF for a highestpriority S-NSSAI, of the multiple S-NSSAIs (such as when the assignmentpolicy indicates there is no single AMF designated to provide service tothe end device for all of the S-NSSAIs in the NSSAI).

As a result, the intelligent AMF assignment service may improve networkresource utilization in a network. For example, the intelligent AMFassignment service may minimize redirection, which reduces networkresource consumption. Additionally, adding RAN and core networkconditions into the AMF selection process provides an end-to-end view ofthe network and improves the initial selection result.

FIG. 1 is a diagram illustrating an exemplary environment 100 in whichan exemplary embodiment of the application-based access control servicemay be implemented. As illustrated, environment 100 includes an accessnetwork 110 and a core network 150. Access network 110 includes accessdevices 115, and core network 150 includes core devices 155. Environment100 further includes UE 180.

The number, the type, and the arrangement of network devices in accessnetwork 110 and core network 150, as illustrated and described, areexemplary. The number of UE devices 180 is also exemplary. A networkdevice, a network element, or a network function (referred to hereinsimply as a network device) may be implemented according to one ormultiple network architectures (e.g., a client device, a server device,a peer device, a proxy device, a cloud device, a virtualized function,and/or another type of network architecture (e.g., Software DefinedNetworking (SDN), virtual, logical, network slicing, etc.)).Additionally, a network device may be implemented according to variouscomputing architectures, such as centralized, distributed, cloud (e.g.,elastic, public, private, etc.), edge, fog, and/or another type ofcomputing architecture. Access devices 115 and core devices 155 may eachinclude a network device.

Environment 100 includes communication links between the networkdevices, and between UE 180 and network devices. Environment 100 may beimplemented to include wired, optical, and/or wireless communicationlinks among the network devices and the networks illustrated. Acommunicative connection via a communication link may be direct orindirect. For example, an indirect communicative connection may involvean intermediary device and/or an intermediary network not illustrated inFIG. 1 . A direct communicative connection may not involve anintermediary device and/or an intermediary network. The number and thearrangement of communication links illustrated in environment 100 areexemplary.

Environment 100 may include various planes of communication including,for example, a control plane, a user plane, and a network managementplane. Environment 100 may include other types of planes ofcommunication. A message communicated in support of theapplication-based access control service may use at least one of theseplanes of communication. Additionally, an interface of a network devicemay be modified in order to support the communication (e.g.,transmission and reception of messages, information elements (IE),attribute value pairs (AVPs), etc.) between network devices and theapplication-based access control service, as described herein. Accordingto various exemplary implementations, the interface may be aservice-based interface or a reference point-based interface.

Access network 110 may establish and maintain, with participation fromUE 180, an over-the-air channel with UE 180; and maintain backhaulchannels with core network 150. Access network 110 may conveyinformation through these channels, from UE 180 to core network 150 andvice versa. Access network 110 may include one or multiple networks ofone or multiple types and technologies. For example, access network 110may include a 5G RAN. In another implementation access network 110 mayinclude a 5G RAN with a Fourth Generation (4G) RAN, a 4.5G RAN, and/oranother type of future generation RAN. By way of further example, accessnetwork 110 may be implemented to include a New Radio (NR) RAN, anEvolved UMTS Terrestrial Radio Access Network (E-UTRAN) of a Long TermEvolution (LTE) network, an LTE-Advanced (LTE-A) network, and/or anLTE-A Pro network, a next generation (NG) RAN, and/or another type ofRAN (e.g., a legacy RAN). Access network 110 may further include othertypes of wireless networks that may provide an on-ramp to access devices115 and/or core network 150. Additionally, according to variousexemplary embodiments, access network 110 may be implemented accordingto various wireless technologies (e.g., radio access technology (RAT),etc.), wireless standards, wireless frequencies/bands/carriers, licensedradio spectrum, unlicensed radio spectrum, and/or other attributes ofradio communication.

Access network 110 may include different and multiple functionalsplitting, such as different combinations of access network 110 and corenetwork 150 including an Evolved Packet Core (EPC) network and/or a 5Gcore (5GC) network, or the splitting of the various layers (e.g.,physical layer, Media Access Control (MAC) layer, Radio Link Control(RLC) layer, and Packet Data Convergence Control (PDCP) layer), planesplitting (e.g., user plane, control plane, etc.), centralized unit (CU)and distributed unit (DU), interface splitting (e.g., F1-U, F1-C, E1,Xn-C, Xn-U, X2-C, Common Public Radio Interface (CPRI), etc.) as well asother types of network services, such as dual connectivity (DC) orhigher (e.g., a secondary cell group (SCG) split bearer service, amaster cell group (MCG) split bearer, an SCG bearer service,non-standalone (NSA), standalone (SA), etc.), CA (e.g., intra-band,inter-band, contiguous, non-contiguous, etc.), network slicing,coordinated multipoint (CoMP), various duplex schemes (e.g., frequencydivision duplex (FDD), time division duplex (TDD), half-duplex FDD(H-FDD), etc.), and/or another type of connectivity service.

Depending on the implementation, access network 110 may include one ormultiple types of network devices, such as access devices 115. Forexample, access devices 115 may include a next generation Node B (gNB),an evolved Node B (eNB), an evolved Long Term Evolution (eLTE) eNB, aradio network controller (RNC), a remote radio head (RRH), a basebandunit (BBU), a small cell node (e.g., a picocell device, a femtocelldevice, a microcell device, a home eNB, a repeater, etc.), or anothertype of wireless node. According to an exemplary embodiment, accessdevice 115 includes logic that provides the intelligent AMF assignmentservice, as described herein.

Core network 150 may include one or multiple networks of one or multipletypes and technologies. According to an exemplary embodiment, corenetwork 150 includes a network to connect and manage different parts ofaccess network 110. For example, core network 150 may be implemented toinclude a 5G core network (also referred to as a next generation core(NGC) network), an EPC of an LTE, a core network of an LTE-Advanced(LTE-A) network, and/or a core network of an LTE-A Pro network. Corenetwork 150 may include a legacy core network.

Depending on the implementation, core network 150 may include varioustypes of network devices, such as core devices 155. For example, coredevices 155 may include a packet gateway (PGW), a serving gateway (SGW),a home subscriber server (HSS), an authentication, authorization, andaccounting (AAA) server, a policy charging and rules function (PCRF), acharging system (CS), a user plane function (UPF), an AMF, a mobilitymanagement entity (MME), a session management function (SMF), a unifieddata management (UDM) device, an authentication server function (AUSF),a network slice selection function (NSSF), a network repository function(NRF), a policy control function (PCF), a network exposure function(NEF), and/or an application function (AF). According to other exemplaryimplementations, core devices 155 may include additional, different,and/or fewer network devices than those described. For example, coredevices 155 may include a non-standard and/or proprietary networkdevice.

UE 180 includes a device that has computational and wirelesscommunication capabilities. Depending on the implementation, UE 180 maybe a mobile device, a portable device, a stationary device, a deviceoperated by a user, or a device not operated by a user. For example, UE180 may be implemented as a Mobile Broadband device, a Machine TypeCommunication (MTC) device, an Internet of Things (IoT) device, anenhanced MTC device (eMTC) (also known as Cat-M1), a NarrowBand IoT(NB-IoT) device, a machine-to-machine (M2M) device, a user device, orother types of wireless end nodes. By way of further example, UE 180 maybe implemented as a smartphone, a personal digital assistant, a tablet,a netbook, a wearable device (e.g., a watch, glasses, etc.), a set topbox, an infotainment system in a vehicle, a vehicle support system, asmart television, a game system, or other types of wireless end devices.

UE 180 may support one or multiple RATs (e.g., 4G, 5G, etc.) and variousportions of the radio spectrum (e.g., multiple frequency bands, multiplecarrier frequencies, licensed, unlicensed, etc.), network slicing, DCservice, and/or other types of connectivity services. Additionally, UE180 may include one or multiple communication interfaces that provideone or multiple (e.g., simultaneous) connections via the same ordifferent RATs, frequency bands, carriers, network slices, and so forth.The multimode capabilities of UE 180 may vary among UEs 180.

FIG. 2 is a diagram illustrating components in a portion 200 ofenvironment 100. As illustrated, environment 200 may include accessnetwork 110 and core network 150. Core network 150 may include multipleAMFs 230-1 through AMF 230-N (e.g., corresponding to care devices 155).As used herein AMF 230 may include a single AMF 230 or an AMF set. An“AMF Set” may include of one or more functionally equivalent AMFs forload balancing purposes. As used herein, an AMF selection and AMF Setselection are used interchangeably. If an AMF Set is selected, then itis assumed an individual AMF, or a most suitable AMF, is selected fromthe set based on, for example, loading information and/or capacity.

In the exemplary configuration of FIG. 2 , access network 110 maycorrespond to an Open RAN (or O-RAN), such as a RAN that implementsarchitectures described under the O-RAN Alliance. Implementationsdescribed herein make use of the O-RAN framework and its interfaces,although other RAN architectures may be used.

Access network 110 may include a gNB 205, a non-real-time RANIntelligent Controller (RIC-non-RT) 220, and a near-real-time RANIntelligent Controller (RIC-near-RT) 225. According to animplementation, gNB 205 may correspond to access device 115 describedabove. gNB 205 may include a distributed architecture, including acentralized unit (CU) 210 and multiple distributed units (DU) 215. Insome implementation, CU 210 and a DU 215 may be co-located.

RIC-non-RT 220 and RIC-near-RT 225 may be implemented as functionallayers of a single component (e.g., a single RIC device) or as separatecomponents. For example, RIC-non-RT 220 may be included in anorchestration layer of a network management system (NMS), whileRIC-near-RT 225 may be included within gNB 205.

RIC-non-RT 220 may provide service and policy management, RAN analytics,and model-training for RIC-near-RT 225. RIC-non-RT 220 may producetrained models and real-time control functions, which may be distributedto RIC-near-RT 225 for runtime execution. According to an implementationdescribed herein, RIC-non-RT 220 may provide network data to RIC-near-RT225 to support computation of an AMF assignment table.

RIC-near-RT 225 may operate at near-real-time response times (e.g.,response times under one second), provide control functionality andinterfaces with CU 210 and/or DU 215 in access network 110. According toan implementation described herein, RIC-near-RT 225 may receive networkdata from RIC-non-RT 220 and compute/update an AMF assignment table.RIC-near-RT 225 may provide the AMF assignment table to gNB 205 (e.g.,CU 210) to perform intelligent selection of an initial AMF 230 in realtime, during UE registration procedure.

FIG. 3A-3C are diagrams illustrating an exemplary process forprovisioning a gNB 205 with an AMF assignment table to support theintelligent AMF assignment service. As illustrated, an environment 300,which is consistent with network portion 200, includes RIC-non-RT 220,RIC-near-RT 225, and CU 210. RIC-non-RT 220 may include or communicatewith a self-organizing network (SON) 305, a service orchestrator (SO)310, and a network data analytics function (NWDAF) 315. CU 210 mayinclude a user plane processing layer (not shown) and a call processing(CU-CP) layer 320.

SON 305 may enable automated optimizations of wireless networks and maybe deployed at a scale to manage wireless networks, such as accessnetwork 110. SON functions may be used to enable discovery andoptimization of access devices (e.g., access devices 115, gNB 205, etc.)neighbor lists, modification of antenna tilts or directions to improvecoverage or capacity, changes to handoff parameters to reduce handoverdrops, adjustments to transmission power, and/or other types ofparameters whose optimizations previously required laborious manualprocedures.

SON 305 may obtain various metrics, also referred to as key performanceindicators (KPIs), across a large number of access devices 115 and UEs180, to perform autonomous analysis on the obtained metrics. The resultof the analysis may indicate a change in one or more parameters of anaccess device 115 to optimize (i.e., improve) the functioning of accessdevices 115 in response to changing conditions.

SO 310 may automate sequences of activities, tasks, rules, and policiesneeded for on-demand creation, modification, or removal of network,application, or infrastructure services and resources. SO 310 providesorchestration at a high level, with an end-to-end view of theinfrastructure, networks (e.g., access network 110 and core network150), and applications.

NWDAF 315 may collect analytics information associated with accessnetwork 110 and/or core network 150. For example, NWDAF 315 may collectaccessibility key performance indicators (KPIs, e.g., a radio resourcecontrol (RRC) setup success rate, a radio access bearer (RAB) successrate, etc.), retainability KPIs (e.g., a call drop rate, etc.), mobilityKPIs (e.g., a handover success rate, etc.), service integrity KPIs(e.g., downlink average throughput, downlink maximum throughput, uplinkaverage throughput, uplink maximum throughput, etc.), utilization KPIs(e.g., resource block utilization rate, average processor load, etc.),availability KPIs (e.g., radio network unavailability rate, etc.),traffic KPIs (e.g., downlink traffic volume, uplink traffic volume,average number of users, maximum number of users, a number of voicebearers, a number of video bearers, etc.), response time KPIs (e.g.,latency, packet arrival time, etc.), and/or other types of wirelessnetwork KPIs. In one implementation, NWDAF 315 may provide KPIs relativeto specific AMFs 230, such as mobility management (e.g., number ofattach attempts; number of successful attempts; number of failedattempts, organized by cause), session management (e.g., number ofdefault, dedicated & total bearer activation attempts initiated by AMF;number of successful attempts; number of failed attempts, organized bycause; average, maximum dedicated bearer set up time; etc.); subscribermanagement (e.g., number of subscribers in IDLE and CONNECTED states,organized by PLMN); function management (e.g., alarm counts organized byseverity, such as critical, major, minor) and causes); etc.

As shown in FIG. 3A, environment 300 may include an A1 interface (e.g.,between RIC-non-RT 220 and RIC-near-RT 225) and an E2 interface (e.g.,from RIC-near-RT 225 towards CU-CP 320). The A1 interface is aninterface between an Orchestration/NMS layer containing RIC-non-RT 220and a gNB 205 that includes RIC-near-RT 225. The E2 interface definesinteractions between RIC-near-RT 225 and CU-CP 320 for functionalitysuch as RRC management and mobility management to CU-CP 320.

Referring to FIG. 3B, communications over the A1 interface are shown tosupport creation of an AMF assignment table. Functions of RIC-non-RT 220may forward data 332 for an AMF assignment table. For example,RIC-non-RT 220 may obtain and forward capabilities and capacities ofdifferent network slices and network functions in access network 110and/or core network 150. In one implementation, SON 305 may provide RAN(e.g., access network 110) short term statistical data; SO 310 mayprovide network resource availability and network function readinessdata; and NWDAF 315 may provide session metrics. As further shown inFIG. 3B, RIC-near-RT 225 may further collect local RAN data 334, such asup-to-date radio resource data and recent AMF assignment data observedin the local RAN.

RIC-near-RT 225 may receive forwarded data 332 and apply collected data334 to compute an AMF assignment table 336 (also referred to as an AMFassignment policy). The AMF assignment table is described further belowin connection with, for example, FIG. 4 . The AMF assignment table maybe computed and periodically updated by RIC-near-RT 225. For example,RIC-non-RT 220 may forward data 332 for an AMF assignment table atintervals of several minutes (e.g., less than 60-minute intervals), andRIC-near-RT 225 may compute and/or update the AMF assignment table aftereach interval.

Referring to FIG. 3C, communications over the E2 interface are shown tosupport delivery of the AMF assignment table to a local CU-CP 320. Aftercalculating and/or updating the AMF assignment table, RIC-near-RT 225may push the AMF assignment table to CU-CP 320. As further shown in FIG.3C, CU-CP 320 may use the AMF assignment table to perform an AMFassignment table lookup 340 during a UE attach procedure. Moreparticularly, CU-CP 320 may perform intelligent selection of an initialAMF (e.g., one of AMFs 230) in real time, during an UE registrationprocedure. CU-CP 320 may extract and use Network Slice SelectionAssistance Information (NSSAI), provided by UE 180, and the updated AMFassignment table, provided by RIC-near-RT 225, to identify a best AMF230 for the service or combinations services requested by UE 180. Asdescribed further herein, CU-CP 320 may select the best AMF 230 based onthe UE 180 NSSAI, which is a collection of Single-NSSAIs (S-NSSAI).Using the AMF assignment table, CU-CP 320 may take into accountindividual slice priority, so that higher priority slices are matched toan appropriate AMF 230. CU-CP 320 may then send a Registration Requestmessage for the UE 180 to the selected AMF.

Although FIGS. 3A-3C illustrate one arrangement of an environment 300,in other implementations, environment 300 may contain fewer components,different components, differently-arranged components, or additionalcomponents than depicted in FIGS. 3A-3C. For example, in anotherimplementation, RIC-non-RT 220, RIC-near-RT 225, CU 210, SON 305, SO310, and NWDAF 315 may be parts of a management and orchestrationframework. Thus, communications described above in connection with FIGS.3A-3C may use different communications interfaces to exchange data andprovide the AMF assignment table than described above. Alternatively, oradditionally, one or more components of environment 300 may perform oneor more other tasks described as being performed by one or more othercomponents of environment 300.

FIG. 4 is a diagram illustrating an exemplary embodiment of an AMFassignment policy for the intelligent AMF assignment service in the formof an AMF assignment table 400. As illustrated, table 400 may include anS-NSSAI field 410, and AMF field 420, and a slice priority field 430. Asfurther illustrated, table 400 includes records 440-1 through 440-X(also referred to as records 440, or individually or generally as record440) that each includes a grouping of fields 410, 420, and 430. The AMFassignment policy is illustrated in tabular form for the sake ofdescription. In this regard, AMF assignment policy may be implemented ina data structure different from a table. The data fields and values areexemplary.

AMF assignment table 400 may indicate network slice priorities (e.g.,for available slices in access network 110 and/or core network 150),based on network data from RIC-non-RT 220 and RIC-near-RT 225, to allowgNBs 205 to select an optimal AMF during initial UE registration.S-NSSAI field 410 may store an identifier of a network slice associatedwith S-NSSAI. AMF field 420 may store an identifier or address for anAMF 230 that services a corresponding network slice in S-NSSAI field410. Slice priority field 430 may store a network slice priority value(e.g., where higher values have higher priority).

Referring to record 440-1, an AMF 230 (e.g., “AMF=w”) is designated tohandle UEs 180 that do not provide any S-NSSAI (e.g., S-NSSAI field 410includes no data). Thus, UEs 180 with no S-NSSAI may be assigned adefault set of slice identifiers.

Referring to record 440-2, an exemplary implementation introduces a“Default S-NSSAI,” which can be provisioned into all UEs 180 (e.g.,during device manufacturing). To support onboarding of such UEs 180 thatdo not receive further provisioning before coming online (e.g.,requesting a connection to access network 110), CU-CP 320 may use table400 to assign a specific set of network resources for these UEs,including a specific AMF (e.g., “AMF=x”). That is, AMF assignment table400 defines which AMF 230 will handle UEs 180 with a default S-NSSAI.

Each selection choice (e.g., each record 440) is assigned a priority(e.g., in slice priority field 430) so that higher priority slices canbe assigned an appropriate AMF 230 over lower priority slices (e.g., inthe case where there is no common AMF 230 for all slices requested by UE180). For example, referring to records 440-3 and 440-4, if UE 180requested to use S-NSSAI=a and S-NSSAI=b, and there is no single AMF 230that is available to handle both of those network slices, then the CU-CP320 would select the AMF 230 for the S-NSSAI with the higher selectionpriority. In this example, of records 440-3 and 440-4, CU-CP 320 wouldselect “AMF=z” because of the higher slice priority (“5”) over “AMF=y.”

According to other exemplary implementations, table 400 may storeadditional, fewer, and/or different instances of AMF assignment policyin support of the application-based access control service, as describedherein. For example, in other implementations, AMF table 400 may includeAMF set information. Furthermore, table 400 could be computed andupdated on a regional basis to accommodate maximum flexibility. That is,AMF assignment policies for one geographic area (e.g., Raleigh-Durham,N.C.) may be different than AMF assignment policies for anothergeographic area (e.g., metropolitan New York).

FIG. 5 is a signal flow diagram of an exemplary UE attach procedureusing the intelligent AMF assignment service in a portion 500 of networkenvironment 100. Network portion 500 may include UE 180, CU 210, DU 215,and AMF 230-2.

In step 1, UE 180 sends an RRC Connection Request message to DU 215. TheRRC Connection Request message may include, among other information, aninformation element (IE) with NSSAI for UE 180. The NSSAI may includeone or more provisioned S-NSSAIs or a default S-NSSAI (e.g., configuredat the time of device manufacture). In step 2, DU 215 includes the RRCmessage and the corresponding low layer configuration for UE 180 in anInitial Uplink (UL) RRC Message Transfer message to CU 210. In step 3,CU 210 allocates a unique ID for UE 180 (e.g., unique within CU 210) andgenerates an RRC Connection Setup message towards UE 180. The RRCConnection Setup message is encapsulated in a Downlink (DL) RRC MessageTransfer message. In step 4, DU 215 sends the RRC Connection Setupmessage to UE 180. In step 5, UE 180 sends an RRC Connection SetupComplete message to DU 215. In step 6, DU 215 encapsulates the RRCConnection Setup Complete message in an UL RRC message transfer messageand sends the message to CU 210.

At step 6A, CU 210 (e.g., CU-CP 320) applies an AMF assignment table(e.g., AMF assignment table 400) to perform a real-time lookup procedurefor UE 180. More particularly, CU 210 may identify one or more S-NSSAIsassociated with UE 180 and identify any records (e.g., records 440) withmatching S-NSSAIs. CU 210 may then identify particular AMFs (e.g., inAMF field 420) that service the S-NSSAIs associated with UE 180, anddetermine, based on priorities in table 400 (e.g., in slice priorityfield 430), the AMF 230 corresponding to the highest priority to serviceUE 180. Assume in the example of FIG. 5 that CU 210 selects AMF 230-2 toservice UE 180.

In step 7, CU 210 sends an Initial UE message to the selected AMF 230-2.In step 8, AMF 230-2 sends an Initial UE Context Setup Request messageto CU 210, and the context setup procedure continues on to steps 9through 18, as shown in FIG. 5 , whereby an initial UE context isestablished between UE 180 and the selected AMF 230-2 according to knownmessage sequences.

Although FIG. 5 illustrates an exemplary process of the intelligent AMFassignment service, according to other exemplary embodiments, theprocess may include additional, different, and/or fewer steps. Forexample, in another implementation, UE 180 may provide NSSAI separatelyfrom an RRC Connection Request message. In another example, UE mayprovide NSSAI in the RRC Connection Setup Complete message of step 5.

FIG. 6 is a diagram illustrating exemplary components of a device 600that may be included in one or more of the devices described herein. Forexample, device 600 may correspond to components included in accessdevices 115, core devices 155, UE device 180, gNB 205, RIC-non-RT 220,RIC-near-RT 225, or AMF 230. As illustrated in FIG. 6 , device 600includes a bus 605, a processor 610, a memory/storage 615 that storessoftware 620, a communication interface 625, an input 630, and an output635. According to other embodiments, device 600 may include fewercomponents, additional components, different components, and/or adifferent arrangement of components than those illustrated in FIG. 6 anddescribed herein.

Bus 605 includes a path that permits communication among the componentsof device 600. For example, bus 605 may include a system bus, an addressbus, a data bus, and/or a control bus. Bus 605 may also include busdrivers, bus arbiters, bus interfaces, clocks, and so forth.

Processor 610 includes one or multiple processors, microprocessors, dataprocessors, co-processors, application specific integrated circuits(ASICs), controllers, programmable logic devices, chipsets,field-programmable gate arrays (FPGAs), application specificinstruction-set processors (ASIPs), system-on-chips (SoCs), centralprocessing units (CPUs) (e.g., one or multiple cores), microcontrollers,and/or some other type of component that interprets and/or executesinstructions and/or data. Processor 610 may be implemented as hardware(e.g., a microprocessor, etc.), a combination of hardware and software(e.g., a SoC, an ASIC, etc.), may include one or multiple memories(e.g., cache, etc.), etc.

Processor 610 may control the overall operation or a portion ofoperation(s) performed by device 600. Processor 610 may perform one ormultiple operations based on an operating system and/or variousapplications or computer programs (e.g., software 620). Processor 610may access instructions from memory/storage 615, from other componentsof device 600, and/or from a source external to device 600 (e.g., anetwork, another device, etc.). Processor 610 may perform an operationand/or a process based on various techniques including, for example,multithreading, parallel processing, pipelining, interleaving, etc.

Memory/storage 615 includes one or multiple memories and/or one ormultiple other types of storage mediums. For example, memory/storage 615may include one or multiple types of memories, such as, a random accessmemory (RAM), a dynamic random access memory (DRAM), a static randomaccess memory (SRAM), a cache, a read only memory (ROM), a programmableread only memory (PROM), an erasable PROM (EPROM), an electrically EPROM(EEPROM), a single in-line memory module (SIMM), a dual in-line memorymodule (DIMM), a flash memory (e.g., 2D, 3D, NOR, NAND, etc.), a solidstate memory, and/or some other type of memory. Memory/storage 615 mayinclude a hard disk (e.g., a magnetic disk, an optical disk, amagneto-optic disk, a solid state disk, etc.), a Micro-ElectromechanicalSystem (MEMS)-based storage medium, and/or a nanotechnology-basedstorage medium. Memory/storage 615 may include drives for reading fromand writing to the storage medium.

Memory/storage 615 may be external to and/or removable from device 600,such as, for example, a Universal Serial Bus (USB) memory stick, adongle, a hard disk, mass storage, off-line storage, or some other typeof storing medium (e.g., a compact disk (CD), a digital versatile disk(DVD), a Blu-Ray disk (BD), etc.). Memory/storage 615 may store data,software, and/or instructions related to the operation of device 600.

Software 620 includes an application or a program that provides afunction and/or a process. As an example, with respect to access device115 (e.g., CU 210 of gNB 205, etc.), software 620 may include anapplication that, when executed by processor 610, provides a function ofthe intelligent AMF assignment service, as described herein.Additionally, with another network device (e.g., RIC-non-RT 220,RIC-near-RT 225, etc.), software 620 may include an application that,when executed by processor 610, provides a function of the intelligentAMF assignment service, as described herein. Software 620 may alsoinclude firmware, middleware, microcode, hardware description language(HDL), and/or other form of instruction. Software 620 may also bevirtualized. Software 620 may further include an operating system (OS)(e.g., Windows, Linux, Android, proprietary, etc.).

Communication interface 625 permits device 600 to communicate with otherdevices, networks, systems, and/or the like. Communication interface 625includes one or multiple wireless interfaces and/or wired interfaces.For example, communication interface 625 may include one or multipletransmitters and receivers, or transceivers. Communication interface 625may operate according to a protocol stack and a communication standard.Communication interface 625 may include an antenna. Communicationinterface 625 may include various processing logic or circuitry (e.g.,multiplexing/de-multiplexing, filtering, amplifying, converting, errorcorrection, application programming interface (API), etc.).Communication interface 625 may be implemented as a point-to-pointinterface, a service based interface, etc.

Input 630 permits an input into device 600. For example, input 630 mayinclude a keyboard, a mouse, a display, a touchscreen, a touchlessscreen, a button, a switch, an input port, speech recognition logic,and/or some other type of visual, auditory, tactile, etc., inputcomponent. Output 635 permits an output from device 600. For example,output 635 may include a speaker, a display, a touchscreen, a touchlessscreen, a light, an output port, and/or some other type of visual,auditory, tactile, etc., output component.

As previously described, a network device may be implemented accordingto various computing architectures (e.g., in a cloud, etc.) andaccording to various network architectures (e.g., a virtualizedfunction, etc.). Device 600 may be implemented in the same manner. Forexample, device 600 may be instantiated, spun up, spun down, or undergoa life-cycle, using well-known virtualization techniques in apublic/private cloud or other type of network.

Device 600 may perform a process and/or a function, as described herein,in response to processor 610 executing software 620 stored bymemory/storage 615. By way of example, instructions may be read intomemory/storage 615 from another memory/storage 615 (not shown) or readfrom another device (not shown) via communication interface 625. Theinstructions stored by memory/storage 615 cause processor 610 to performa process described herein. Alternatively, for example, according toother implementations, device 600 performs a process described hereinbased on the execution of hardware (processor 610, etc.).

FIG. 7 is a flow diagram illustrating an exemplary process 700 of anexemplary embodiment of the intelligent AMF assignment service.According to an exemplary embodiment, a network device of access network110 performs steps of process 700. For example, the network device maybe CU 210 of gNB 205. Additionally, for example, processor 610 mayexecute software 620 to perform a step illustrated in FIG. 7 anddescribed herein. Additionally, or alternatively, a step illustrated inFIG. 7 may be performed by execution of only hardware.

In block 705, network data may be received from a RIC-non-RT. Forexample, RIC-non-RT 220 may obtain network data from SON 305, SO 310,and/or NWDAF 315 that may indicate capabilities and capacities ofdifferent network slices of network environment 100. RIC-non-RT 220 mayperiodically forward the network data to RIC-near-RT 225.

In block 710, local RAN data may be retrieved from a RIC-near-RT. Forexample, RIC-near-RT 225 may collect local RAN data, such as up-to-dateradio resources and recent AMF assignment data observed in the local RANthat includes RIC-near-RT 225.

In block 715, an AMF assignment policy or information may be generatedand/or updated. For example, RIC-near-RT 225 may generate or update AMFassignment table 400 and forward AMF assignment table 400 to gNB 205(e.g., CU 210).

In block 720, the AMF assignment policy may be stored. For example, gNB205 (e.g., CU 210) may receive AMF assignment table 400 from RIC-near-RT225 and store AMF assignment table 400 in a local memory (e.g.,memory/storage 615).

In block 725, a registration request for a UE may be received. Forexample, UE 180 may initiate an RRC Connection Request that is receivedat gNB 205 (e.g., DU 215). The RRC Connection Request may include NSSAIfor UE 180. Alternatively, NSSAI may be missing from the RRC ConnectionRequest.

In block 730, NSSAI may be extracted from the connection request. Forexample, gNB 205 (e.g., CU 210) may extract NSSAI, if available, fromthe RRC Connection Request. The NSSAI may include one or more S-NSSAIsrequested by UE 180.

In block 735, it may be determined if there is an S-NSSAI match. Forexample, gNB 205 (e.g., CU 210) may compare the S-NSSAIs for UE 180 withAMF assignment table 400 to determine if one or more corresponding AMFscan be associated with the S-NSSAIs for UE 180.

If there is an S-NSSAI match in the assignment policy (block 735—yes),an AMF for the S-NSSAI with the highest slice priority may be selected(block 740). For example, assume the RCC Connection Request from UE 180includes multiple S-NSSAIs. gNB 205 (e.g., CU 210) may use AMFassignment table 400 to identify corresponding records 440 that have thesame S-NSSAIs as included in the RCC Connection Request. If table 400indicates all of the S-NSSAIs identified by UE 180 can be serviced by asingle AMF, CU 210 may select the appropriate AMF identifier (e.g., fromAMF field 420) to service UE 180. If there is no single AMF in table 400that is designated to provide services for all of the S-NSSAIsidentified by UE 180, then the CU 210 may select a best available AMF230. That is, CU 210 may identify the highest priority S-NSSAI in theRCC Connection Request (e.g., based on table 400) and select thecorresponding AMF identifier from table 400 to service UE 180. Theselected AMF 230 may service UE 180 for all of the S-NSSAIs identifiedin the RCC Connection Request.

If there is not an S-NSSAI match (block 735—no), in block 745, an AMFdesignated for missing NSSAI may be selected. For example, if no NSSAI(or no S-NSSAIs) are identified in the RRC Connection Request from UE180, gNB 205 (e.g., CU 210) may select the AMF assigned for UEs 180 withmissing NSSAI.

FIG. 7 illustrates an exemplary process 700 of the AMF assignmentservice, however, according to other embodiments, process 700 mayinclude additional operations, fewer operations, and/or differentoperations than those illustrated in FIG. 7 , and described herein. Forexample, the network device may perform block 735 in response toreceiving a message from another network device during an attachmentprocedure. Additionally, for example, the network device may use othertypes of information (e.g., subscription information, end devicecapability information, etc.) to determine the network slice priority.

As set forth in this description and illustrated by the drawings,reference is made to “an exemplary embodiment,” “an embodiment,”“embodiments,” etc., which may include a particular feature, structureor characteristic in connection with an embodiment(s). However, the useof the phrase or term “an embodiment,” “embodiments,” etc., in variousplaces in the specification does not necessarily refer to allembodiments described, nor does it necessarily refer to the sameembodiment, nor are separate or alternative embodiments necessarilymutually exclusive of other embodiment(s). The same applies to the term“implementation,” “implementations,” etc.

The foregoing description of embodiments provides illustration, but isnot intended to be exhaustive or to limit the embodiments to the preciseform disclosed. Accordingly, modifications to the embodiments describedherein may be possible. For example, various modifications and changesmay be made thereto, and additional embodiments may be implemented,without departing from the broader scope of the invention as set forthin the claims that follow. The description and drawings are accordinglyto be regarded as illustrative rather than restrictive.

The terms “a,” “an,” and “the” are intended to be interpreted to includeone or more items. Further, the phrase “based on” is intended to beinterpreted as “based, at least in part, on,” unless explicitly statedotherwise. The term “and/or” is intended to be interpreted to includeany and all combinations of one or more of the associated items. Theword “exemplary” is used herein to mean “serving as an example.” Anyembodiment or implementation described as “exemplary” is not necessarilyto be construed as preferred or advantageous over other embodiments orimplementations.

In addition, while series of signal flows and blocks have been describedwith regard to the processes illustrated in FIGS. 5 and 7 , the order ofthe signal flows and blocks may be modified according to otherembodiments. Further, non-dependent blocks may be performed in parallel.Additionally, other processes described in this description may bemodified and/or non-dependent operations may be performed in parallel.

Embodiments described herein may be implemented in many different formsof software executed by hardware. For example, a process or a functionmay be implemented as “logic,” a “component,” or an “element.” Thelogic, the component, or the element, may include, for example, hardware(e.g., processor 610, etc.), or a combination of hardware and software(e.g., software 620).

Embodiments have been described without reference to the specificsoftware code because the software code can be designed to implement theembodiments based on the description herein and commercially availablesoftware design environments and/or languages. For example, varioustypes of programming languages including, for example, a compiledlanguage, an interpreted language, a declarative language, or aprocedural language may be implemented.

Use of ordinal terms such as “first,” “second,” “third,” etc., in theclaims to modify a claim element does not by itself connote anypriority, precedence, or order of one claim element over another, thetemporal order in which acts of a method are performed, the temporalorder in which instructions executed by a device are performed, etc.,but are used merely as labels to distinguish one claim element having acertain name from another element having a same name (but for use of theordinal term) to distinguish the claim elements.

Additionally, embodiments described herein may be implemented as anon-transitory computer-readable storage medium that stores data and/orinformation, such as instructions, program code, a data structure, aprogram module, an application, a script, or other known or conventionalform suitable for use in a computing environment. The program code,instructions, application, etc., is readable and executable by aprocessor (e.g., processor 610) of a device. A non-transitory storagemedium includes one or more of the storage mediums described in relationto memory/storage 615.

To the extent the aforementioned embodiments collect, store or employpersonal information of individuals, it should be understood that suchinformation shall be collected, stored, and used in accordance with allapplicable laws concerning protection of personal information.Additionally, the collection, storage and use of such information can besubject to consent of the individual to such activity, for example,through well known “opt-in” or “opt-out” processes as can be appropriatefor the situation and type of information. Collection, storage, and useof personal information can be in an appropriately secure mannerreflective of the type of information, for example, through variousencryption and anonymization techniques for particularly sensitiveinformation.

No element, act, or instruction set forth in this description should beconstrued as critical or essential to the embodiments described hereinunless explicitly indicated as such.

All structural and functional equivalents to the elements of the variousaspects set forth in this disclosure that are known or later come to beknown to those of ordinary skill in the art are expressly incorporatedherein by reference and are intended to be encompassed by the claims. Noclaim element of a claim is to be interpreted under 35 U.S.C. § 112(f)unless the claim element expressly includes the phrase “means for” or“step for.”

What is claimed is:
 1. A method comprising: storing, in a radio accessnetwork (RAN), an assignment policy for selecting an access and mobilitymanagement function (AMF) from a group of available AMFs, wherein theassignment policy includes network slice priorities for availablenetwork slices in the RAN; receiving, by the RAN, a request messageinitiated by an end device, wherein the request message includes asingle-Network Slice Selection Assistance Information (S-NSSAI) field;and selecting, by the RAN, an AMF associated with a highest priorityS-NSSAI in the S-NSSAI field, based on the network slice priorities inthe assignment policy.
 2. The method of claim 1, further comprising:receiving, from a core network, the assignment policy.
 3. The method ofclaim 1, further comprising: obtaining, by the RAN, network data thatindicates capabilities for the available network slices, wherein theassignment policy is based on the network data.
 4. The method of claim3, wherein receiving the network data includes receiving the networkdata from one or more of: a self-organizing network (SON), a serviceorchestrator (SO), or a network data analytics function (NWDAF).
 5. Themethod of claim 1, further comprising: collecting, by the RAN, local RANdata, including recent AMF assignment data; and sending the assignmentpolicy to an access device of the RAN.
 6. The method of claim 1, whereinselecting the AMF includes selecting the AMF when the assignment policyindicates there is no single AMF designated to provide service to theend device.
 7. The method of claim 1, wherein storing by the RANincludes: storing by a control plane function of a next generation NodeB (gNB).
 8. The method of claim 1, further comprising: generating, bythe RAN, the assignment policy.
 9. A system comprising: an access deviceof a radio access network (RAN) including a processor configured to:store an assignment policy for selecting an access and mobilitymanagement function (AMF) from a group of available AMFs, wherein theassignment policy includes network slice priorities for availablenetwork slices in the RAN, receive a request message initiated by an enddevice, wherein the request message includes a single-Network SliceSelection Assistance Information (S-NSSAI) field, and select, an AMFassociated with a highest priority S-NSSAI in the S-NSSAI field, basedon the network slice priorities in the assignment policy.
 10. The systemof claim 9, wherein the processor is further configured to: receivenetwork data that indicates capacities for the available network slices,wherein the assignment policy is based on the network data.
 11. Thesystem of claim 10, wherein the processor is further configured toreceive the network data from one or more of: a self-organizing network(SON), a service orchestrator (SO), or a network data analytics function(NWDAF).
 12. The system of claim 9, wherein the processor is furtherconfigured to: collect local RAN data, including recent AMF assignmentdata.
 13. The system of claim 9, wherein the processor is furtherconfigured to: send the assignment policy to multiple other accessdevices.
 14. The system of claim 9, wherein the processor is furtherconfigured to: receive the assignment policy from one of a core networkdevice or a RAN device.
 15. The system of claim 9, wherein the accessdevice includes a next generation Node B (gNB).
 16. The system of claim9, wherein the assignment policy further includes priorities for enddevices that provide a default S-NSSAI and priorities for end devicesthat provide no S-NSSAI.
 17. A non-transitory computer-readable storagemedium storing instructions executable by a processor of a networkdevice, which when executed cause the network device to: store anassignment policy for selecting an access and mobility managementfunction (AMF) from a group of available AMFs, wherein the assignmentpolicy includes network slice priorities for available network slices ina radio access network (RAN); receive a request message initiated by anend device, wherein the request message includes a single-Network SliceSelection Assistance Information (S-NSSAI) field; and select, an AMFassociated with a highest priority S-NSSAI in the S-NSSAI field, basedon the network slice priorities in the assignment policy.
 18. Thenon-transitory computer-readable storage medium of claim 17, furtherstoring instructions executable by the processor of the network deviceto: periodically receive an updated assignment policy for selecting theAMF from the group of available AMFs.
 19. The non-transitorycomputer-readable storage medium of claim 17, wherein the assignmentpolicy further includes priorities for end devices that provide adefault S-NSSAI and priorities for end devices that provide no S-NSSAI.20. The non-transitory computer-readable storage medium of claim 17,further storing instructions executable by the processor of the networkdevice to: send, to the selected AMF, a registration request for the enddevice.